Take-home Exercise 2

Animations in R

2.3 Step-by-Step Data Visualisation Preparation

2.3.1 Install and load required libraries

packages = c('ggiraph','plotly','DT','patchwork','gganimate','tidyverse','readxl','gifski','gapminder','sf','tmap','rgdal','ggplot2','scales','magick')
for (p in packages){
  if(!require(p, character.only = T)){
    install.packages(p)
    }
  library(p,character.only = T)
}

2.3.2 Read CSV file

population <- read.csv("data/respopagesextod2011to2020.csv")

Group population count by PA, AG, Sex and Time

population_summary <- population %>% group_by(Sex,PA,AG,Time) %>% summarise(Pop = sum(Pop))

2.3.5 Extract Starting Numeric Value of Age Group for Sorting

population_summary$BandMinAge <- gsub('([0-9]+).*','\\1',population_summary$AG)
population_summary$BandMinAge <- as.numeric(population_summary$BandMinAge)
population_summary <- population_summary[order(population_summary$BandMinAge, decreasing = FALSE),]
population_summary$PlanningArea <- toupper(population_summary$PA)

2.3.10 Plot Age-Sex Pyramid for Singapore

SGpyramid <- ggplot(population_summary, aes(x = reorder(AG,BandMinAge), y = Pop, fill = Sex)) + 
  geom_bar_interactive(data=subset(population_summary, Sex == "Females"), stat = "identity", aes(y=Pop)) + 
  geom_text_interactive(data = subset(population_summary, Sex == "Females"), aes(y = Pop,label=''), 
      size = 4, hjust = -0.1) +
  geom_bar_interactive(stat = "identity", data = subset(population_summary, Sex == "Males"), aes(y=Pop * (-1)) )+
  scale_y_continuous(name="Population", breaks=c(-150000,-100000,-50000,0,50000,100000,150000), labels = c("150,000","100,000","50,000","0","50,000","100,000","150,000") ) +
  coord_flip()+
  labs(title = "Singapore | Year: {frame_time}", x = "Age")+
  theme(panel.background = element_rect(fill = 'white'))+
  transition_time(Time)+
  ease_aes('linear')
SG<- image_read(animate(SGpyramid, width = 500, height=500))

2.3.10 Plot Age-Sex Pyramid for each PA

countPA = 0
for (area in unique(population_summary$PA)){
  
  d <- subset(population_summary, PA == area)
  plot.new()
  PAplot<- (ggplot(d, aes(x = reorder(AG,BandMinAge), y = Pop, fill = Sex)) + 
    geom_bar_interactive(data=subset(d, Sex == "Females"), stat = "identity", aes(y=Pop)) + 
    geom_text_interactive(data = subset(d, Sex == "Females"), aes(y = Pop,label=''), 
                          size = 4, hjust = -0.1) +
    geom_bar_interactive(stat = "identity", data = subset(d, Sex == "Males"), aes(y=Pop * (-1)) )+
    scale_y_continuous(
    name="Population", 
    breaks=c(-15000,-10000,-5000,0,5000,10000,15000), 
    labels = abs(c(-15000,-10000,-5000,0,5000,10000,15000)), 
    limits=c(-15000,15000)) +
    coord_flip()+
    labs(title = paste(area, " {frame_time}"), x = "Age")+
    theme(panel.background = element_rect(fill = 'white'))+
    transition_time(Time)+
    ease_aes('linear'))
  GIF<- image_read(animate(PAplot, width = 500, height=500))
  countPA = countPA + 1
  assign(paste0("GIF",countPA),GIF)
}